AI startup Thinking Machines clinches capital and a major chip supply deal from Nvidia


A smartphone with a displayed NVIDIA logo is placed on a computer motherboard in this illustration taken March 6, 2023. REUTERS/Dado Ruvic/Illustration

March 10 (Reuters) - AI startup Thinking ⁠Machines Lab said on Tuesday it has struck a multi-year partnership with ⁠Nvidia that will see it receive a significant investment and procure ‌at least one gigawatt of the chipmaker's next-generation processors.

Financial terms of the deal were not disclosed.

Under the agreement, Thinking Machines - founded last year by former OpenAI Chief Technology Officer Mira Murati - will deploy Nvidia's ​upcoming Vera Rubin systems starting early next year. ⁠The computing power will primarily be ⁠used to train the startup's artificial intelligence models.

Industry executives have said 1 gigawatt ⁠of ‌computing power, enough to power roughly 750,000 U.S. homes, can cost around $50 billion.

The deal will help Thinking Machines compete with larger rivals in building ⁠powerful AI systems, and underscores the industry's eagerness to scale ​computing capacity.

Thinking Machines quickly ‌became one of Silicon Valley's most closely watched AI startups after raising ⁠about $2 billion in ​a seed funding round led by Andreessen Horowitz that valued the company at $12 billion. Nvidia was also an investor in the round.

The startup has recently been seeking to raise ⁠more in a new funding round that could value ​it at tens of billions of dollars, sources told Reuters earlier.

The company has recently seen several departures, including co-founder and former Chief Technology Officer Barret Zoph and co-founder ⁠Luke Metz, who both returned to their former employer OpenAI amid fierce competition for AI talent.

The partnership also highlights Nvidia’s growing role as a financier of the startups that rely on its AI chips.

It has made a recent $30 billion investment in ​OpenAI andinvested $10 billion inAnthropic, while also supplying the graphics ⁠processing units (GPUs) used to train and run their models, a dynamic that some industry ​analysts say creates a circular flow of capital and ‌computing resources. That in turn has given ​rise to comparisons with the late 1990s tech bubble.

(Reporting by Krystal Hu in San Francisco; Additional reporting by Deepa Seetharaman; Editing by Edwina Gibbs)

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